Environmentalbert Environmental

🚀 EnvironmentalBERT-environmental模型卡片

本模型是一個專門用於ESG領域環境文本分類的語言模型，基於特定論文進行訓練，能有效檢測環境文本樣本，為環境相關的文本分析提供了強大支持。

🚀 快速開始

可參考Medium上的這些教程，獲取關於模型使用、大規模分析和微調的指南。

你可以使用管道進行文本分類：

基礎用法

from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 
tokenizer_name = "ESGBERT/EnvironmentalBERT-environmental"
model_name = "ESGBERT/EnvironmentalBERT-environmental"
 
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, max_len=512)
 
pipe = pipeline("text-classification", model=model, tokenizer=tokenizer) # set device=0 to use GPU
 
# See https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.pipeline
print(pipe("Scope 1 emissions are reported here on a like-for-like basis against the 2013 baseline and exclude emissions from additional vehicles used during repairs.", padding=True, truncation=True))

✨ 主要特性

基於這篇論文開發的EnvironmentalBERT-environmental語言模型，以EnvironmentalBERT-base模型為起點，在一個包含2000個樣本的環境數據集上進行了額外的微調，能夠更好地對ESG領域的環境文本進行分類。

📚 詳細文檔

更多詳細信息可在論文中找到：

@article{Schimanski23ESGBERT,
    title={{Bridiging the Gap in ESG Measurement: Using NLP to Quantify Environmental, Social, and Governance Communication}},
    author={Tobias Schimanski and Andrin Reding and Nico Reding and Julia Bingler and Mathias Kraus and Markus Leippold},
    year={2023},
    journal={Available on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4622514},
}

📄 許可證

本模型採用Apache-2.0許可證。

📦 數據集

• ESGBERT/environmental_2k

🏷️ 標籤

• ESG
• environmental